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A new, improved version of the Big Data Specialization will become available on June 6! As such, enrollment for this course and all courses in this original Big Data Specialization will close on June 6.
The original Big Data Specialization will continue to run until September 2016, when the Capstone will be offered for learners in this version of the Specialization.
If you are in the middle of the Specialization and have purchased the entire original Big Data Specialization before June 6, Coursera will reach out to you to offer you the option of staying in the original Specialization or taking the new version.
If you are just getting started on this Specialization, we recommend that you wait until June 6 to enroll in the new version.
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This course is for novice programmers or business people who'd like to understand the core tools used to wrangle and analyze big data. With no prior experience, you'll have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques, such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis processes.

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Introduction to Map/Reduce

This module will introduce Map/Reduce concepts and practice. You will learn about the big idea of Map/Reduce and you will learn how to design, implement, and execute tasks in the map/reduce framework. You will also learn the trade-offs in map/reduce and how that motivates other tools.